RNA-seq analysis.
RNA-seq analysis for Jagesh Shah group at Longwood.
Contact Lorena Pantano (lpantano@hsph.harvard.edu) for additional details.
The most recent update of this html document occurred: Thu Feb 2 16:54:53 2017
The sections below provide code to reproduce the included results and plots.
## Warning: package 'knitr' was built under R version 3.3.2Overview
2017-02-02 16:55:01 INFO::Using gene counts calculated from the Sailfish transcript counts.Differential expression
Dispersion estimates
Comparison: mice_model_jck_wt
out of 28948 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 5626, 19%
LFC < 0 (down) : 4691, 16%
outliers [1] : 0, 0%
low counts [2] : 6665, 23%
(mean count < 1)
[1] see ‘cooksCutoff’ argument of ?results
[2] see ‘independentFiltering’ argument of ?results
NULL
Differential expression file at: mice_model_jck_wt_de.csv
Normalized counts matrix file at: mice_model_jck_wt_log2_counts.csv
MA plot plot
Volcano plot
QC for DE genes p-values/variance
Most significand, FDR< 0.1 and log2FC > 0 : 10317
Plots most significand
Plot top 9 genes
Top DE genes
| baseMean | log2FoldChange | lfcSE | stat | pvalue | padj | absMaxLog2FC | |
|---|---|---|---|---|---|---|---|
| ENSMUSG00000014813 | 173.6603 | 2.1507312 | 0.1068010 | 20.13775 | 0 | 0 | 2.1507312 |
| ENSMUSG00000038071 | 259.2756 | 3.4667747 | 0.1951606 | 17.76370 | 0 | 0 | 3.4667747 |
| ENSMUSG00000036853 | 610.5610 | 2.0357935 | 0.1305086 | 15.59893 | 0 | 0 | 2.0357935 |
| ENSMUSG00000046546 | 994.8930 | 1.0829969 | 0.0700300 | 15.46476 | 0 | 0 | 1.0829969 |
| ENSMUSG00000022123 | 270.4489 | 1.2116727 | 0.0872539 | 13.88675 | 0 | 0 | 1.2116727 |
| ENSMUSG00000026822 | 3151.2868 | 4.3673037 | 0.3159933 | 13.82087 | 0 | 0 | 4.3673037 |
| ENSMUSG00000039405 | 1055.6664 | 0.9514464 | 0.0691527 | 13.75863 | 0 | 0 | 0.9514464 |
| ENSMUSG00000031390 | 731.0540 | 0.9262546 | 0.0679541 | 13.63058 | 0 | 0 | 0.9262546 |
| ENSMUSG00000048834 | 102.9005 | -1.6088336 | 0.1188446 | -13.53729 | 0 | 0 | 1.6088336 |
| ENSMUSG00000040405 | 1252.0868 | 4.6338388 | 0.3496244 | 13.25376 | 0 | 0 | 4.6338388 |
| ENSMUSG00000053113 | 491.0256 | 3.5768235 | 0.2715283 | 13.17293 | 0 | 0 | 3.5768235 |
| ENSMUSG00000001131 | 244.7676 | 4.3056384 | 0.3344138 | 12.87518 | 0 | 0 | 4.3056384 |
| ENSMUSG00000031904 | 196.7504 | 1.1868056 | 0.0927694 | 12.79308 | 0 | 0 | 1.1868056 |
| ENSMUSG00000029811 | 543.3703 | 2.7326751 | 0.2140976 | 12.76369 | 0 | 0 | 2.7326751 |
| ENSMUSG00000085180 | 128.8999 | 1.4768996 | 0.1175146 | 12.56780 | 0 | 0 | 1.4768996 |
| ENSMUSG00000050335 | 1880.2186 | 1.8094092 | 0.1444747 | 12.52406 | 0 | 0 | 1.8094092 |
| ENSMUSG00000061947 | 410.6397 | 3.7060789 | 0.2958967 | 12.52491 | 0 | 0 | 3.7060789 |
| ENSMUSG00000028364 | 460.6414 | 1.9161503 | 0.1602581 | 11.95665 | 0 | 0 | 1.9161503 |
| ENSMUSG00000057751 | 129.0649 | 3.1432037 | 0.2646103 | 11.87861 | 0 | 0 | 3.1432037 |
| ENSMUSG00000074653 | 146.4168 | 1.3726445 | 0.1160311 | 11.82997 | 0 | 0 | 1.3726445 |
Here, I only considered the condition to get the DE genes. These will contain genes where the mean on each condition is different, and will help to detect genes that are always UP or DOWN.
Comparison: mice_model_late
out of 29001 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up) : 915, 3.2%
LFC < 0 (down) : 1189, 4.1%
outliers [1] : 10, 0.034%
low counts [2] : 12667, 44%
(mean count < 8)
[1] see ‘cooksCutoff’ argument of ?results
[2] see ‘independentFiltering’ argument of ?results
NULL
Differential expression file at: mice_model_late_de.csv
Normalized counts matrix file at: mice_model_late_log2_counts.csv
MA plot plot
Volcano plot
QC for DE genes p-values/variance
Most significand, FDR< 0.05 and log2FC > 0.5 : 1089
Plots most significand
Plot top 9 genes
Top DE genes
| baseMean | log2FoldChange | lfcSE | stat | pvalue | padj | symbol | description | absMaxLog2FC | |
|---|---|---|---|---|---|---|---|---|---|
| ENSMUSG00000029304 | 114749.89505 | -3.3671436 | 0.3772822 | 86.30123 | 0 | 0.0e+00 | Spp1 | secreted phosphoprotein 1 | 3.3671436 |
| ENSMUSG00000052392 | 633.69960 | 1.7788144 | 0.2096200 | 72.09577 | 0 | 0.0e+00 | Acot4 | acyl-CoA thioesterase 4 | 1.7788144 |
| ENSMUSG00000022037 | 18586.52065 | -2.6294328 | 0.3702635 | 68.51329 | 0 | 0.0e+00 | Clu | clusterin | 2.6294328 |
| ENSMUSG00000022010 | 12995.60801 | -2.0083478 | 0.2540145 | 66.03906 | 0 | 0.0e+00 | Tsc22d1 | TSC22 domain family, member 1 | 2.0083478 |
| ENSMUSG00000023019 | 10901.79058 | 1.3714163 | 0.1997442 | 64.40358 | 0 | 0.0e+00 | Gpd1 | glycerol-3-phosphate dehydrogenase 1 (soluble) | 1.3714163 |
| ENSMUSG00000058952 | 352.58400 | -2.1009773 | 0.3293173 | 64.27045 | 0 | 0.0e+00 | Cfi | complement component factor i | 2.1009773 |
| ENSMUSG00000021228 | 1129.42917 | 2.1216502 | 0.2994171 | 60.95581 | 0 | 0.0e+00 | Acot3 | acyl-CoA thioesterase 3 | 2.1216502 |
| ENSMUSG00000002565 | 2610.44797 | -1.3796893 | 0.1852228 | 59.53631 | 0 | 0.0e+00 | Scin | scinderin | 1.3796893 |
| ENSMUSG00000024479 | 2033.08115 | -1.3939719 | 0.1922656 | 58.31450 | 0 | 0.0e+00 | Mal2 | mal, T cell differentiation protein 2 | 1.3939719 |
| ENSMUSG00000029811 | 543.37028 | -2.6294878 | 0.4654234 | 55.78897 | 0 | 0.0e+00 | Aoc1 | amine oxidase, copper-containing 1 | 2.6294878 |
| ENSMUSG00000015852 | 114.67300 | -3.1380608 | 0.6290703 | 52.75188 | 0 | 1.0e-07 | Fcrls | Fc receptor-like S, scavenger receptor | 3.1380608 |
| ENSMUSG00000029484 | 581.93663 | -1.8376379 | 0.2676036 | 52.32848 | 0 | 2.0e-07 | Anxa3 | annexin A3 | 1.8376379 |
| ENSMUSG00000031482 | 2486.60168 | 0.9853763 | 0.1641964 | 51.00154 | 0 | 3.0e-07 | Slc25a15 | solute carrier family 25 (mitochondrial carrier ornithine transporter), member 15 | 0.9853763 |
| ENSMUSG00000053063 | 56.71267 | -3.6571623 | 0.6138824 | 48.74406 | 0 | 8.0e-07 | Clec12a | C-type lectin domain family 12, member a | 3.6571623 |
| ENSMUSG00000038642 | 1086.93525 | -2.7162279 | 0.4504279 | 47.95844 | 0 | 1.0e-06 | Ctss | cathepsin S | 2.7162279 |
| ENSMUSG00000026255 | 2411.40769 | 0.8457319 | 0.1548358 | 47.16852 | 0 | 1.4e-06 | Efhd1 | EF hand domain containing 1 | 0.8457319 |
| ENSMUSG00000033860 | 1758.48435 | -3.0693263 | 0.4946513 | 47.10698 | 0 | 1.4e-06 | Fgg | fibrinogen gamma chain | 3.0693263 |
| ENSMUSG00000036594 | 3672.02577 | -2.1823271 | 0.3872259 | 46.94062 | 0 | 1.4e-06 | H2-Aa | histocompatibility 2, class II antigen A, alpha | 2.1823271 |
| ENSMUSG00000035649 | 313.74368 | -0.3660899 | 0.2337200 | 46.60849 | 0 | 1.6e-06 | Zcchc7 | zinc finger, CCHC domain containing 7 | 0.3660899 |
| ENSMUSG00000037348 | 726.05890 | 0.9785023 | 0.1854403 | 46.07993 | 0 | 1.9e-06 | Paqr7 | progestin and adipoQ receptor family member VII | 0.9785023 |
GO ontology of DE genes (log2FC > 0.5 and FDR < 0.05 ): 1089
| ID | Description | GeneRatio | BgRatio | pvalue | p.adjust | qvalue | |
|---|---|---|---|---|---|---|---|
| GO:0050900 | GO:0050900 | leukocyte migration | 48/991 | 263/20996 | 0.0000000 | 0.0000000 | 0.0000000 |
| GO:0050865 | GO:0050865 | regulation of cell activation | 63/991 | 467/20996 | 0.0000000 | 0.0000000 | 0.0000000 |
| GO:0002250 | GO:0002250 | adaptive immune response | 50/991 | 345/20996 | 0.0000000 | 0.0000000 | 0.0000000 |
| GO:0044282 | GO:0044282 | small molecule catabolic process | 40/991 | 246/20996 | 0.0000000 | 0.0000000 | 0.0000000 |
| GO:0051186 | GO:0051186 | cofactor metabolic process | 43/991 | 322/20996 | 0.0000000 | 0.0000001 | 0.0000001 |
| GO:0019884 | GO:0019884 | antigen processing and presentation of exogenous antigen | 13/991 | 33/20996 | 0.0000000 | 0.0000001 | 0.0000001 |
| GO:0071345 | GO:0071345 | cellular response to cytokine stimulus | 51/991 | 448/20996 | 0.0000000 | 0.0000005 | 0.0000004 |
| GO:0001819 | GO:0001819 | positive regulation of cytokine production | 44/991 | 357/20996 | 0.0000000 | 0.0000005 | 0.0000004 |
| GO:0030198 | GO:0030198 | extracellular matrix organization | 31/991 | 208/20996 | 0.0000000 | 0.0000010 | 0.0000007 |
| GO:0006897 | GO:0006897 | endocytosis | 52/991 | 475/20996 | 0.0000000 | 0.0000011 | 0.0000008 |
| GO:0044236 | GO:0044236 | multicellular organism metabolic process | 19/991 | 95/20996 | 0.0000001 | 0.0000044 | 0.0000033 |
| GO:0009636 | GO:0009636 | response to toxic substance | 24/991 | 153/20996 | 0.0000002 | 0.0000108 | 0.0000080 |
| GO:1990267 | GO:1990267 | response to transition metal nanoparticle | 16/991 | 78/20996 | 0.0000006 | 0.0000251 | 0.0000187 |
| GO:1901615 | GO:1901615 | organic hydroxy compound metabolic process | 45/991 | 440/20996 | 0.0000010 | 0.0000388 | 0.0000288 |
| GO:0010038 | GO:0010038 | response to metal ion | 27/991 | 204/20996 | 0.0000013 | 0.0000489 | 0.0000364 |
| GO:0043410 | GO:0043410 | positive regulation of MAPK cascade | 44/991 | 434/20996 | 0.0000017 | 0.0000596 | 0.0000443 |
| GO:0042493 | GO:0042493 | response to drug | 27/991 | 216/20996 | 0.0000039 | 0.0001225 | 0.0000910 |
| GO:0015711 | GO:0015711 | organic anion transport | 37/991 | 356/20996 | 0.0000062 | 0.0001807 | 0.0001343 |
| GO:0048146 | GO:0048146 | positive regulation of fibroblast proliferation | 13/991 | 65/20996 | 0.0000089 | 0.0002461 | 0.0001829 |
| GO:0051259 | GO:0051259 | protein oligomerization | 46/991 | 493/20996 | 0.0000090 | 0.0002461 | 0.0001829 |
| GO:0006837 | GO:0006837 | serotonin transport | 7/991 | 21/20996 | 0.0000332 | 0.0007227 | 0.0005371 |
| GO:0072593 | GO:0072593 | reactive oxygen species metabolic process | 26/991 | 231/20996 | 0.0000379 | 0.0008031 | 0.0005968 |
| GO:0072331 | GO:0072331 | signal transduction by p53 class mediator | 16/991 | 114/20996 | 0.0000897 | 0.0016539 | 0.0012291 |
| GO:0097191 | GO:0097191 | extrinsic apoptotic signaling pathway | 25/991 | 230/20996 | 0.0000937 | 0.0017131 | 0.0012731 |
| GO:0015748 | GO:0015748 | organophosphate ester transport | 12/991 | 71/20996 | 0.0001116 | 0.0019528 | 0.0014512 |
| GO:0051092 | GO:0051092 | positive regulation of NF-kappaB transcription factor activity | 15/991 | 106/20996 | 0.0001342 | 0.0022214 | 0.0016508 |
| GO:0006766 | GO:0006766 | vitamin metabolic process | 11/991 | 63/20996 | 0.0001583 | 0.0025181 | 0.0018714 |
| GO:0097006 | GO:0097006 | regulation of plasma lipoprotein particle levels | 10/991 | 54/20996 | 0.0001889 | 0.0029333 | 0.0021799 |
| GO:1901342 | GO:1901342 | regulation of vasculature development | 25/991 | 243/20996 | 0.0002232 | 0.0032958 | 0.0024493 |
| GO:0007229 | GO:0007229 | integrin-mediated signaling pathway | 12/991 | 77/20996 | 0.0002470 | 0.0035781 | 0.0026591 |
| GO:0006081 | GO:0006081 | cellular aldehyde metabolic process | 10/991 | 57/20996 | 0.0002999 | 0.0041588 | 0.0030907 |
| GO:0006577 | GO:0006577 | amino-acid betaine metabolic process | 5/991 | 14/20996 | 0.0003248 | 0.0043442 | 0.0032284 |
| GO:0010998 | GO:0010998 | regulation of translational initiation by eIF2 alpha phosphorylation | 5/991 | 14/20996 | 0.0003248 | 0.0043442 | 0.0032284 |
| GO:0051051 | GO:0051051 | negative regulation of transport | 40/991 | 477/20996 | 0.0003322 | 0.0044306 | 0.0032927 |
| GO:0051495 | GO:0051495 | positive regulation of cytoskeleton organization | 20/991 | 181/20996 | 0.0003657 | 0.0048056 | 0.0035713 |
| GO:0018108 | GO:0018108 | peptidyl-tyrosine phosphorylation | 28/991 | 296/20996 | 0.0003916 | 0.0050876 | 0.0037809 |
| GO:0006968 | GO:0006968 | cellular defense response | 5/991 | 15/20996 | 0.0004683 | 0.0056929 | 0.0042307 |
| GO:0001503 | GO:0001503 | ossification | 33/991 | 377/20996 | 0.0005094 | 0.0061258 | 0.0045524 |
| GO:0044089 | GO:0044089 | positive regulation of cellular component biogenesis | 35/991 | 409/20996 | 0.0005298 | 0.0063001 | 0.0046819 |
| GO:0043648 | GO:0043648 | dicarboxylic acid metabolic process | 12/991 | 84/20996 | 0.0005615 | 0.0065952 | 0.0049013 |
| GO:1901264 | GO:1901264 | carbohydrate derivative transport | 8/991 | 41/20996 | 0.0005701 | 0.0066395 | 0.0049342 |
| GO:0050673 | GO:0050673 | epithelial cell proliferation | 32/991 | 364/20996 | 0.0005711 | 0.0066395 | 0.0049342 |
| GO:0060390 | GO:0060390 | regulation of SMAD protein import into nucleus | 5/991 | 16/20996 | 0.0006549 | 0.0074229 | 0.0055164 |
| GO:2000351 | GO:2000351 | regulation of endothelial cell apoptotic process | 8/991 | 42/20996 | 0.0006755 | 0.0075809 | 0.0056338 |
| GO:0008360 | GO:0008360 | regulation of cell shape | 15/991 | 123/20996 | 0.0006902 | 0.0077269 | 0.0057423 |
| GO:0002507 | GO:0002507 | tolerance induction | 6/991 | 25/20996 | 0.0008903 | 0.0092323 | 0.0068611 |
| GO:0002643 | GO:0002643 | regulation of tolerance induction | 5/991 | 17/20996 | 0.0008919 | 0.0092323 | 0.0068611 |
| GO:0015695 | GO:0015695 | organic cation transport | 5/991 | 17/20996 | 0.0008919 | 0.0092323 | 0.0068611 |
This will detect genes that change differently over time in the two conditions.
Clustering in common patterns
We used diana function inside cluster R package to separate genes using the expression correlation with time. Clusters with more than 3 genes are shown. Significant genes were those with log2FC bigger than 0.1 and FDR < 5%. The file with the information of this analysis is clusters_genes.tsv.
Using expression
Working with 1089 genes
Working with 1037 genes after filtering
Using fold change with two conditions
Working with 1089 genes
Working with 907 genes after filtering
Using fold change at each time point
Working with 1089 genes
Working with 1059 genes after filtering
R Session Info
(useful if replicating these results)
R version 3.3.1 (2016-06-21)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.12.1 (Sierra)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats4 methods stats graphics grDevices utils
[8] datasets base
other attached packages:
[1] vsn_3.40.0 DEGreport_1.11.2
[3] quantreg_5.29 SparseM_1.72
[5] dplyr_0.5.0 cluster_2.0.5
[7] org.Mm.eg.db_3.3.0 AnnotationDbi_1.34.4
[9] clusterProfiler_3.0.5 DOSE_2.10.7
[11] gridExtra_2.2.1 logging_0.7-103
[13] tximport_1.0.3 DESeq2_1.12.4
[15] SummarizedExperiment_1.2.3 Biobase_2.32.0
[17] GenomicRanges_1.24.3 GenomeInfoDb_1.8.7
[19] IRanges_2.6.1 S4Vectors_0.10.3
[21] BiocGenerics_0.18.0 pheatmap_1.0.8
[23] CHBUtils_0.1 edgeR_3.14.0
[25] limma_3.28.21 gplots_3.0.1
[27] reshape_0.8.6 ggplot2_2.2.0
[29] myRfunctions_0.1 knitr_1.15.1
[31] rmarkdown_1.1
loaded via a namespace (and not attached):
[1] bitops_1.0-6 matrixStats_0.51.0 RColorBrewer_1.1-2
[4] tools_3.3.1 affyio_1.42.0 R6_2.2.0
[7] rpart_4.1-10 KernSmooth_2.23-15 Hmisc_3.17-4
[10] DBI_0.5-1 lazyeval_0.2.0 colorspace_1.2-7
[13] nnet_7.3-12 preprocessCore_1.34.0 Nozzle.R1_1.1-1
[16] chron_2.3-47 graph_1.50.0 labeling_0.3
[19] topGO_2.24.0 caTools_1.17.1 scales_0.4.1
[22] affy_1.50.0 readr_1.0.0 genefilter_1.54.2
[25] stringr_1.1.0 digest_0.6.10 foreign_0.8-67
[28] XVector_0.12.1 htmltools_0.3.5 highr_0.6
[31] RSQLite_1.0.0 BiocInstaller_1.22.3 BiocParallel_1.6.6
[34] gtools_3.5.0 acepack_1.3-3.3 GOSemSim_1.30.3
[37] RCurl_1.95-4.8 magrittr_1.5 GO.db_3.3.0
[40] Formula_1.2-1 Matrix_1.2-7.1 Rcpp_0.12.7
[43] munsell_0.4.3 stringi_1.1.2 yaml_2.1.14
[46] zlibbioc_1.18.0 plyr_1.8.4 qvalue_2.4.2
[49] grid_3.3.1 gdata_2.17.0 DO.db_2.9
[52] lattice_0.20-34 splines_3.3.1 annotate_1.50.1
[55] locfit_1.5-9.1 igraph_1.0.1 geneplotter_1.50.0
[58] reshape2_1.4.1 codetools_0.2-15 XML_3.98-1.4
[61] evaluate_0.10 latticeExtra_0.6-28 data.table_1.9.6
[64] MatrixModels_0.4-1 gtable_0.2.0 tidyr_0.6.0
[67] assertthat_0.1 xtable_1.8-2 coda_0.19-1
[70] survival_2.39-5 tibble_1.2 GSEABase_1.34.1